Machine learning control of nonlinear fiber dynamics

Mathilde Hary; Lauri Salmela; Mehdi Mabed; John M. Dudley; Goëry Genty

doi:10.1117/12.2609474

9 March 2022 Machine learning control of nonlinear fiber dynamics

Mathilde Hary, Lauri Salmela, Mehdi Mabed, John M. Dudley, Goëry Genty

Proceedings Volume PC12019, AI and Optical Data Sciences III; PC120190Z (2022) https://doi.org/10.1117/12.2609474
Event: SPIE OPTO, 2022, San Francisco, California, United States

Abstract

We use machine learning methods to control the spectral broadening experienced by femtosecond pulses in a highly nonlinear fiber. Combining a programmable spectral filter with a genetic algorithm or neural network allows us to optimize the nonlinear propagation dynamics to generate an on-demand target spectrum. Our approach is generic and can be adapted to a wide range of optical fibers and pump pulses. We expect our results to provide significant advances for adaptative control and tailored light sources.

Conference Presentation

Citation Download Citation

Mathilde Hary, Lauri Salmela, Mehdi Mabed, John M. Dudley, and Goëry Genty "Machine learning control of nonlinear fiber dynamics", Proc. SPIE PC12019, AI and Optical Data Sciences III, PC120190Z (9 March 2022); https://doi.org/10.1117/12.2609474

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